Abstract

BackgroundThe diffusion of health technologies from translational research to reimbursement depends on several factors included the results of health economic analysis. Recent research identified several flaws in health economic concepts. Additionally, the heterogeneous viewpoints of participating stakeholders are rarely systematically addressed in current decision-making. Multi-criteria Decision Analysis (MCDA) provides an opportunity to tackle these issues. The objective of this study was to review applications of MCDA methods in decisions addressing the trade-off between costs and benefits.MethodsUsing basic steps of the PRISMA guidelines, a systematic review of the healthcare literature was performed to identify original research articles from January 1990 to April 2014. Medline, PubMed, Springer Link and specific journals were searched. Using predefined categories, bibliographic records were systematically extracted regarding the type of policy applications, MCDA methodology, criteria used and their definitions.Results22 studies were included in the analysis. 15 studies (68 %) used direct MCDA approaches and seven studies (32 %) used preference elicitation approaches. Four studies (19 %) focused on technologies in the early innovation process. The majority (18 studies - 81 %) examined reimbursement decisions. Decision criteria used in studies were obtained from the literature research and context-specific studies, expert opinions, and group discussions. The number of criteria ranged between three up to 15. The most frequently used criteria were health outcomes (73 %), disease impact (59 %), and implementation of the intervention (40 %). Economic criteria included cost-effectiveness criteria (14 studies, 64 %), and total costs/budget impact of an intervention (eight studies, 36 %). The process of including economic aspects is very different among studies. Some studies directly compare costs with other criteria while some include economic consideration in a second step.ConclusionsIn early innovation processes, MCDA can provide information about stakeholder preferences as well as evidence needs in further development. However, only a minority of these studies include economic features due to the limited evidence. The most important economic criterion cost-effectiveness should not be included from a technical perspective as it is already a composite of costs and benefit. There is a significant lack of consensus in methodology employed by the various studies which highlights the need for guidance on application of MCDA at specific phases of an innovation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-015-0930-0) contains supplementary material, which is available to authorized users.

Highlights

  • The diffusion of health technologies from translational research to reimbursement depends on several factors included the results of health economic analysis

  • In early innovation processes, Multi-criteria Decision Analysis (MCDA) can provide information about stakeholder preferences as well as evidence needs in further development

  • There is a significant lack of consensus in methodology employed by the various studies which highlights the need for guidance on application of MCDA at specific phases of an innovation

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Summary

Introduction

The diffusion of health technologies from translational research to reimbursement depends on several factors included the results of health economic analysis. Reimbursement decisions of public health care regulate access and usage of new health technologies [1] These decisions are the bottle neck for medical innovation in many countries with both economic and social implications [2, 3]. Manufacturers increasingly use health economic tools [4,5,6,7,8] to assess investment decisions in the development process of medical technologies. The rationale behind these concepts is to compare the costs and the medical benefit of medical technologies. QALYs are widely used by HTA agencies, academia and industry because it is assumed as an objective measure to compare technologies

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